The present exemplary embodiment relates to image processing. It finds particular application in connection with the automated correction of digital images for red eye.
Red eye is a common problem in photographic images. It occurs whenever a flash is used and the light reflecting from the human retina makes the eyes appear red instead of their natural color. Recognizing this problem, camera manufacturers have attempted to minimize or inhibit red eye by equipping cameras with the ability to emit one or more pre-flashes of light immediately prior to completion of the actual photograph. These pre-flashes are intended to constrict the subject's pupils to minimize light incident on the retina and reflected therefrom. Although cameras equipped with pre-flash hardware can alleviate red eye problems, they are not always well received since the red eye artifact is not always prevented. They also tend to consume much more energy, induce a significant delay between pushing the button and taking the photograph, and result in people blinking the eyes. Red eye has become more prevalent and severe as cameras have been made smaller with integrated flashes. The small size coupled with the built-in nature of the flash requires placement of the flash in close proximity to the objective lens. Thus, a greater portion of the reflected light from a subject's retinas enters the object lens and is recorded.
Techniques have been developed for the detection and correction of red eye in images. In one method, an operator visually scans all images and marks those images including red eye for further processing. The processing typically involves modifying the red pixels in the identified red eye. Efforts to eliminate or reduce operator involvement have resulted in automated processes that attempt to detect red eye based upon color, size, and shape criteria. When a red eye is detected, the automated process applies a correction to the red area. Given that the color red is very common, and that red eye is not present in a great many images (e.g., those not taken using a flash, those not including human subjects, etc.), false-positives are common. Thus, red buttons, a piece of red candy, and the like, may all be misidentified as red eye using such automated red eye detection techniques.
Some red eye correction techniques rely on face detection. However, face detection is in itself a difficult task. It does not perform well for non-frontal, rotated and occluded faces. In such cases these methods tend to perform poorly.